Package: GSelection 0.1.0
Sayanti Guha Majumdar
GSelection: Genomic Selection
Genomic selection is a specialized form of marker assisted selection. The package contains functions to select important genetic markers and predict phenotype on the basis of fitted training data using integrated model framework (Guha Majumdar et. al. (2019) <doi:10.1089/cmb.2019.0223>) developed by combining one additive (sparse additive models by Ravikumar et. al. (2009) <doi:10.1111/j.1467-9868.2009.00718.x>) and one non-additive (hsic lasso by Yamada et. al. (2014) <doi:10.1162/NECO_a_00537>) model.
Authors:
GSelection_0.1.0.tar.gz
GSelection_0.1.0.tar.gz(r-4.5-noble)GSelection_0.1.0.tar.gz(r-4.4-noble)
GSelection_0.1.0.tgz(r-4.4-emscripten)GSelection_0.1.0.tgz(r-4.3-emscripten)
GSelection.pdf |GSelection.html✨
GSelection/json (API)
| # Install 'GSelection' in R: |
| install.packages('GSelection', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- GS - Genotypic and phenotypic simulated dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:2e4a3bf36f. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 12 2024 |
| R-4.5-linux | OK | Oct 12 2024 |
Exports:feature.selectiongenomic.predictionhsic.var.ensemblehsic.var.rcvREDspam.var.ensemblespam.var.rcv
Dependencies:gdatagtoolslatticeMatrixpenalizedRcppRcppArmadilloRcppEigenSAMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Genomic Selection | GSelection-package GSelection |
| Genomic Feature Selection | feature.selection |
| Genomic Prediction | genomic.prediction |
| Genotypic and phenotypic simulated dataset | GS |
| Error Variance Estimation in Genomic Prediction | hsic.var.ensemble |
| Error Variance Estimation in Genomic Prediction | hsic.var.rcv |
| Redundancy Rate | RED |
| Error Variance Estimation in Genomic Prediction | spam.var.ensemble |
| Error Variance Estimation in Genomic Prediction | spam.var.rcv |